personal memory agent
observe/transcribe: split parakeet into platform dispatcher + linux arm
Renames the Mac-only parakeet backend to _parakeet_coreml and introduces
_parakeet_nemo for Linux x86_64 (nvidia/parakeet-tdt-0.6b-v{2,3} via
nemo_toolkit[asr] + torch). The public observe.transcribe.parakeet
module becomes a thin dispatcher that routes on sys.platform +
platform.machine(); BACKEND_REGISTRY and callers are unchanged.
NeMo does not expose per-word confidence on the timestamps=True path,
so the Linux arm emits probability=1.0 as a sentinel and reports
per_word_confidence=False in model metadata.
make install now branches by OS: Darwin runs make parakeet-helper, Linux
runs uv sync --extra parakeet-nemo. Either failure mode prints
"parakeet backend unavailable: ..." to stderr and exits 0 so the rest
of the install completes.
Test-env fix included: conftest.py's cv2 and sklearn stubs now carry a
ModuleSpec, because pulling transformers into the venv via the NeMo
extra causes importlib.util.find_spec(...) probes that crash on stub
modules with __spec__ is None. The settings/transcribe API baseline is
refreshed for the new parakeet metadata.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
+5252
-409
+8
Makefile
+8
Makefile
···
73
73
exit 1; \
74
74
fi; \
75
75
}
76
+
@OS_NAME=$$(uname -s); \
77
+
if [ "$$OS_NAME" = "Darwin" ]; then \
78
+
$(MAKE) parakeet-helper || (echo 'parakeet backend unavailable: helper build failed' >&2; true); \
79
+
elif [ "$$OS_NAME" = "Linux" ]; then \
80
+
$(UV) sync --extra parakeet-nemo || (echo 'parakeet backend unavailable: uv sync --extra parakeet-nemo failed' >&2; true); \
81
+
else \
82
+
true; \
83
+
fi
76
84
77
85
# Directories where AI coding agents look for skills
78
86
SKILL_DIRS := journal/.agents/skills journal/.claude/skills
+3
-3
observe/transcribe/__init__.py
+3
-3
observe/transcribe/__init__.py
···
94
94
"settings": [],
95
95
},
96
96
"parakeet": {
97
-
"label": "Parakeet - Local processing (Apple Silicon, optional helper)",
98
-
"description": "On-device speech recognition via FluidAudio + Parakeet TDT; requires `make parakeet-helper`",
97
+
"label": "Parakeet - Local processing (Apple Silicon CoreML or Linux NeMo)",
98
+
"description": "On-device speech recognition via Parakeet TDT; macOS uses a FluidAudio/CoreML helper, Linux uses NeMo + torch. Requires `make install`.",
99
99
"env_key": None,
100
-
"settings": ["model_version", "timeout_sec"],
100
+
"settings": ["model_version", "device", "timeout_sec"],
101
101
},
102
102
}
103
103
+374
observe/transcribe/_parakeet_coreml.py
+374
observe/transcribe/_parakeet_coreml.py
···
1
+
# SPDX-License-Identifier: AGPL-3.0-only
2
+
# Copyright (c) 2026 sol pbc
3
+
4
+
"""Parakeet STT backend via a Swift helper.
5
+
6
+
This backend shells out to `observe/transcribe/parakeet_helper/` for FluidAudio
7
+
inference, then rebuilds repo-standard statements with
8
+
`observe.transcribe.utils.build_statements_from_acoustic`.
9
+
"""
10
+
11
+
from __future__ import annotations
12
+
13
+
import difflib
14
+
import json
15
+
import logging
16
+
import os
17
+
import string
18
+
import subprocess
19
+
import tempfile
20
+
from pathlib import Path
21
+
22
+
import numpy as np
23
+
import soundfile as sf
24
+
25
+
from observe.transcribe.utils import build_statements_from_acoustic
26
+
27
+
_VERSION_CACHE: dict[str, dict] = {}
28
+
_DEFAULT_MODEL_VERSION = "v3"
29
+
_DEFAULT_TIMEOUT_SEC = 120.0
30
+
_DEFAULT_CACHE_DIR = (
31
+
Path.home() / "Library/Application Support/solstone/parakeet/models"
32
+
)
33
+
_VALID_MODEL_VERSIONS = frozenset({"v2", "v3"})
34
+
_PUNCTUATION_TOKENS = frozenset(string.punctuation) | frozenset(
35
+
{"—", "…", "’", "‘", "“", "”"}
36
+
)
37
+
_HELPER_ENV_KEY = "SOLSTONE_PARAKEET_HELPER"
38
+
39
+
40
+
def transcribe(
41
+
audio: np.ndarray,
42
+
sample_rate: int,
43
+
config: dict,
44
+
) -> list[dict]:
45
+
"""Transcribe audio by invoking the Parakeet helper and rebuilding statements."""
46
+
model_version, cache_dir, timeout_sec = _validate_config(config)
47
+
helper_path = _resolve_helper_path()
48
+
model_info = get_model_info(config)
49
+
50
+
temp_path = None
51
+
try:
52
+
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as handle:
53
+
temp_path = Path(handle.name)
54
+
55
+
audio_int16 = (np.clip(audio, -1.0, 1.0) * 32767).astype(np.int16)
56
+
sf.write(temp_path, audio_int16, sample_rate, format="WAV", subtype="PCM_16")
57
+
58
+
argv = [
59
+
str(helper_path),
60
+
"--cache-dir",
61
+
str(cache_dir),
62
+
"--model",
63
+
model_version,
64
+
str(temp_path),
65
+
]
66
+
67
+
try:
68
+
result = subprocess.run(
69
+
argv,
70
+
check=False,
71
+
capture_output=True,
72
+
text=True,
73
+
timeout=timeout_sec,
74
+
)
75
+
except subprocess.TimeoutExpired as exc:
76
+
raise RuntimeError(
77
+
f"Parakeet helper timed out after {timeout_sec:.1f}s. Rebuild with "
78
+
f"'make parakeet-helper', increase transcribe.parakeet.timeout_sec, "
79
+
f"or set ${_HELPER_ENV_KEY} to a different helper build."
80
+
) from exc
81
+
82
+
if result.returncode != 0:
83
+
stderr = (result.stderr or "").strip()
84
+
try:
85
+
stderr_json = json.loads(stderr) if stderr else {}
86
+
except json.JSONDecodeError:
87
+
stderr_json = {}
88
+
message = stderr_json.get("message") or stderr or "unknown helper failure"
89
+
90
+
if result.returncode == 2:
91
+
raise RuntimeError(
92
+
f"Parakeet helper rejected validated arguments (internal bug — file an issue): {message}"
93
+
)
94
+
if result.returncode == 3:
95
+
raise RuntimeError(
96
+
f"Parakeet helper could not prepare cache dir {cache_dir}: {message}"
97
+
)
98
+
if result.returncode == 4:
99
+
raise RuntimeError(
100
+
f"Parakeet helper failed to download or load model '{model_version}'. "
101
+
f"Valid values: v2, v3. {message}"
102
+
)
103
+
if result.returncode == 5:
104
+
raise RuntimeError(
105
+
f"Parakeet helper failed to transcribe audio: {message}"
106
+
)
107
+
raise RuntimeError(
108
+
f"Parakeet helper failed with exit code {result.returncode}: {message}"
109
+
)
110
+
111
+
try:
112
+
payload = json.loads(result.stdout)
113
+
except json.JSONDecodeError as exc:
114
+
raise RuntimeError(f"Parakeet helper returned invalid JSON: {exc}") from exc
115
+
if not isinstance(payload, dict):
116
+
raise RuntimeError("Parakeet helper returned a non-object JSON payload")
117
+
118
+
helper_transcript = str(payload.get("transcript", "")).strip()
119
+
token_timings = payload.get("token_timings", [])
120
+
if not token_timings:
121
+
if helper_transcript:
122
+
raise RuntimeError(
123
+
"Parakeet helper returned transcript text without token timings "
124
+
"(internal bug — file an issue)."
125
+
)
126
+
return []
127
+
128
+
words = _collapse_subwords_to_words(token_timings)
129
+
if not words:
130
+
if helper_transcript:
131
+
raise RuntimeError(
132
+
"Parakeet helper returned token timings that collapsed to no words "
133
+
"(internal bug — file an issue)."
134
+
)
135
+
return []
136
+
137
+
acoustic_segments = [
138
+
{
139
+
"id": 1,
140
+
"start": words[0]["start"],
141
+
"end": words[-1]["end"],
142
+
"text": helper_transcript,
143
+
"words": words,
144
+
}
145
+
]
146
+
statements = build_statements_from_acoustic(acoustic_segments)
147
+
for statement in statements:
148
+
statement["speaker"] = None
149
+
150
+
rebuilt_text = " ".join(statement["text"] for statement in statements).strip()
151
+
_log_drift_if_needed(helper_transcript, rebuilt_text)
152
+
153
+
audio_sec = float(payload.get("audio_sec", len(audio) / sample_rate))
154
+
transcribe_ms = int(payload.get("transcribe_ms", 0))
155
+
tx_sec = transcribe_ms / 1000.0
156
+
rtfx = float(payload.get("rtfx", 0.0))
157
+
logging.info(
158
+
f" Transcribed {len(statements)} statements, {audio_sec:.2f}s speech "
159
+
f"in {tx_sec:.2f}s (RTFx: {rtfx:.2f}) [model={model_info['model']}]"
160
+
)
161
+
162
+
return statements
163
+
164
+
finally:
165
+
if temp_path and temp_path.exists():
166
+
temp_path.unlink()
167
+
168
+
169
+
def get_model_info(config: dict) -> dict:
170
+
"""Return Parakeet model metadata for transcript JSONL headers."""
171
+
model_version, _cache_dir, _timeout_sec = _validate_config(config)
172
+
helper_path = _resolve_helper_path()
173
+
version_envelope = _probe_helper_version(helper_path)
174
+
return {
175
+
"model": f"parakeet-tdt-0.6b-{model_version}",
176
+
"device": "ane",
177
+
"compute_type": "coreml_fp16",
178
+
"fluidaudio_version": version_envelope["fluidaudio_version"],
179
+
"helper_hardware": version_envelope["hardware"],
180
+
}
181
+
182
+
183
+
def _resolve_helper_path() -> Path:
184
+
"""Resolve the Parakeet helper path from env override or default build path."""
185
+
env_path = os.getenv(_HELPER_ENV_KEY)
186
+
if env_path:
187
+
candidate = Path(env_path).expanduser().resolve()
188
+
if not candidate.exists():
189
+
raise RuntimeError(
190
+
f"Parakeet helper not found at ${_HELPER_ENV_KEY}={candidate}. "
191
+
f"Run 'make parakeet-helper' or point ${_HELPER_ENV_KEY} at a valid executable."
192
+
)
193
+
if not candidate.is_file() or not os.access(candidate, os.X_OK):
194
+
raise RuntimeError(
195
+
f"Parakeet helper at ${_HELPER_ENV_KEY}={candidate} is not executable. "
196
+
f"Run 'make parakeet-helper', chmod +x the file, or point "
197
+
f"${_HELPER_ENV_KEY} at a valid executable."
198
+
)
199
+
return candidate
200
+
201
+
candidate = (
202
+
Path(__file__).with_name("parakeet_helper")
203
+
/ ".build"
204
+
/ "release"
205
+
/ "parakeet-helper"
206
+
).resolve()
207
+
if (
208
+
not candidate.exists()
209
+
or not candidate.is_file()
210
+
or not os.access(candidate, os.X_OK)
211
+
):
212
+
raise RuntimeError(
213
+
f"Parakeet helper not found at {candidate}. Run 'make parakeet-helper' "
214
+
f"or set ${_HELPER_ENV_KEY} to a valid executable."
215
+
)
216
+
return candidate
217
+
218
+
219
+
def _probe_helper_version(helper_path: Path) -> dict:
220
+
"""Probe and cache the helper version envelope by resolved binary path."""
221
+
cache_key = str(helper_path.resolve())
222
+
if cache_key in _VERSION_CACHE:
223
+
return _VERSION_CACHE[cache_key]
224
+
225
+
try:
226
+
result = subprocess.run(
227
+
[str(helper_path), "--version"],
228
+
check=False,
229
+
capture_output=True,
230
+
text=True,
231
+
timeout=10.0,
232
+
)
233
+
except subprocess.TimeoutExpired as exc:
234
+
raise RuntimeError(
235
+
f"Parakeet helper timed out after 10.0s. Rebuild with "
236
+
f"'make parakeet-helper', increase transcribe.parakeet.timeout_sec, "
237
+
f"or set ${_HELPER_ENV_KEY} to a different helper build."
238
+
) from exc
239
+
240
+
if result.returncode != 0:
241
+
stderr = (result.stderr or "").strip()
242
+
try:
243
+
stderr_json = json.loads(stderr) if stderr else {}
244
+
except json.JSONDecodeError:
245
+
stderr_json = {}
246
+
message = stderr_json.get("message") or stderr or "unknown helper failure"
247
+
if result.returncode == 2:
248
+
raise RuntimeError(
249
+
f"Parakeet helper rejected validated arguments (internal bug — file an issue): {message}"
250
+
)
251
+
if result.returncode == 3:
252
+
raise RuntimeError(
253
+
f"Parakeet helper could not prepare cache dir {_DEFAULT_CACHE_DIR}: {message}"
254
+
)
255
+
if result.returncode == 4:
256
+
raise RuntimeError(
257
+
f"Parakeet helper failed to download or load model '{_DEFAULT_MODEL_VERSION}'. "
258
+
f"Valid values: v2, v3. {message}"
259
+
)
260
+
if result.returncode == 5:
261
+
raise RuntimeError(f"Parakeet helper failed to transcribe audio: {message}")
262
+
raise RuntimeError(
263
+
f"Parakeet helper failed with exit code {result.returncode}: {message}"
264
+
)
265
+
266
+
try:
267
+
payload = json.loads(result.stdout)
268
+
except json.JSONDecodeError as exc:
269
+
raise RuntimeError(
270
+
f"Parakeet helper returned invalid version JSON: {exc}"
271
+
) from exc
272
+
if not isinstance(payload, dict):
273
+
raise RuntimeError("Parakeet helper returned a non-object version payload")
274
+
275
+
_VERSION_CACHE[cache_key] = payload
276
+
return payload
277
+
278
+
279
+
def _collapse_subwords_to_words(token_timings: list[dict]) -> list[dict]:
280
+
"""Collapse helper token timings into repo-standard word dicts."""
281
+
if not token_timings:
282
+
return []
283
+
284
+
words = []
285
+
current_parts: list[str] = []
286
+
current_confidences: list[float] = []
287
+
current_start: float | None = None
288
+
current_end: float | None = None
289
+
290
+
def flush() -> None:
291
+
nonlocal current_parts, current_confidences, current_start, current_end
292
+
if not current_parts or current_start is None or current_end is None:
293
+
current_parts = []
294
+
current_confidences = []
295
+
current_start = None
296
+
current_end = None
297
+
return
298
+
text = "".join(current_parts).lstrip()
299
+
words.append(
300
+
{
301
+
"word": f" {text}",
302
+
"start": current_start,
303
+
"end": current_end,
304
+
"probability": min(current_confidences),
305
+
}
306
+
)
307
+
current_parts = []
308
+
current_confidences = []
309
+
current_start = None
310
+
current_end = None
311
+
312
+
for token in token_timings:
313
+
raw = str(token.get("token", ""))
314
+
is_punctuation = bool(raw) and all(
315
+
char in _PUNCTUATION_TOKENS for char in raw if char
316
+
)
317
+
starts_new = raw.startswith("▁") or raw.startswith(" ")
318
+
319
+
if starts_new and current_parts and not is_punctuation:
320
+
flush()
321
+
322
+
cleaned = raw.lstrip("▁")
323
+
if starts_new:
324
+
cleaned = cleaned.lstrip(" ")
325
+
326
+
current_parts.append(cleaned)
327
+
current_confidences.append(float(token.get("confidence", 0.0)))
328
+
329
+
if not is_punctuation and current_start is None:
330
+
current_start = float(token["start"])
331
+
if not is_punctuation:
332
+
current_end = float(token["end"])
333
+
334
+
flush()
335
+
return words
336
+
337
+
338
+
def _log_drift_if_needed(fluid_transcript: str, rebuilt_text: str) -> None:
339
+
"""Warn when helper text and rebuilt text materially diverge."""
340
+
fluid_transcript = fluid_transcript.strip()
341
+
rebuilt_text = rebuilt_text.strip()
342
+
if not fluid_transcript or not rebuilt_text:
343
+
return
344
+
345
+
ratio = difflib.SequenceMatcher(None, fluid_transcript, rebuilt_text).ratio()
346
+
if ratio < 0.95:
347
+
logging.warning(
348
+
"Parakeet transcript drift detected (ratio=%.3f): helper=%r rebuilt=%r",
349
+
ratio,
350
+
fluid_transcript,
351
+
rebuilt_text,
352
+
)
353
+
354
+
355
+
def _validate_config(config: dict) -> tuple[str, Path, float]:
356
+
"""Validate backend config before spawning the helper."""
357
+
model_version = config.get("model_version", _DEFAULT_MODEL_VERSION)
358
+
if model_version not in _VALID_MODEL_VERSIONS:
359
+
raise ValueError("model_version must be one of: v2, v3")
360
+
361
+
raw_timeout = config.get("timeout_sec", _DEFAULT_TIMEOUT_SEC)
362
+
try:
363
+
timeout_sec = float(raw_timeout)
364
+
except (TypeError, ValueError) as exc:
365
+
raise ValueError(f"timeout_sec must be > 0, got {raw_timeout!r}") from exc
366
+
if timeout_sec <= 0:
367
+
raise ValueError(f"timeout_sec must be > 0, got {raw_timeout!r}")
368
+
369
+
raw_cache_dir = config.get("cache_dir")
370
+
cache_dir = (
371
+
Path(raw_cache_dir).expanduser() if raw_cache_dir else _DEFAULT_CACHE_DIR
372
+
)
373
+
374
+
return model_version, cache_dir, timeout_sec
+222
observe/transcribe/_parakeet_nemo.py
+222
observe/transcribe/_parakeet_nemo.py
···
1
+
# SPDX-License-Identifier: AGPL-3.0-only
2
+
# Copyright (c) 2026 sol pbc
3
+
4
+
"""Parakeet (NeMo) backend for Linux x86_64.
5
+
6
+
Uses nvidia/parakeet-tdt-0.6b-{v2,v3} via nemo_toolkit[asr] and torch.
7
+
First run downloads the model into ~/.cache/huggingface/hub/.
8
+
9
+
NeMo timestamp output does not expose per-word confidence, so this
10
+
backend emits probability=1.0 as a sentinel for each word and reports
11
+
per_word_confidence=False in get_model_info().
12
+
"""
13
+
14
+
from __future__ import annotations
15
+
16
+
import logging
17
+
import tempfile
18
+
import time
19
+
from pathlib import Path
20
+
from typing import Any
21
+
22
+
import numpy as np
23
+
import soundfile as sf
24
+
25
+
from observe.transcribe.utils import build_statements_from_acoustic
26
+
27
+
logging.getLogger("nemo_logger").setLevel(logging.WARNING)
28
+
29
+
_DEFAULT_MODEL_VERSION = "v3"
30
+
_DEFAULT_TIMEOUT_SEC = 120.0
31
+
_DEFAULT_DEVICE = "auto"
32
+
_DEFAULT_PRECISION = "auto"
33
+
_MODEL_IDS = {
34
+
"v2": "nvidia/parakeet-tdt-0.6b-v2",
35
+
"v3": "nvidia/parakeet-tdt-0.6b-v3",
36
+
}
37
+
_MODEL_CACHE: dict[tuple[str, str, str], Any] = {}
38
+
39
+
40
+
def _validate_config(config: dict) -> tuple[str, str, float, str]:
41
+
"""Validate backend configuration."""
42
+
model_version = config.get("model_version", _DEFAULT_MODEL_VERSION)
43
+
if model_version not in _MODEL_IDS:
44
+
raise ValueError("model_version must be one of: v2, v3")
45
+
46
+
device = config.get("device", _DEFAULT_DEVICE)
47
+
if device not in {"auto", "cpu", "cuda"}:
48
+
raise ValueError("device must be one of: auto, cpu, cuda")
49
+
50
+
precision = config.get("precision", _DEFAULT_PRECISION)
51
+
if precision not in {"auto", "float16", "float32"}:
52
+
raise ValueError("precision must be one of: auto, float16, float32")
53
+
54
+
raw_timeout = config.get("timeout_sec", _DEFAULT_TIMEOUT_SEC)
55
+
try:
56
+
timeout_sec = float(raw_timeout)
57
+
except (TypeError, ValueError) as exc:
58
+
raise ValueError(f"timeout_sec must be > 0, got {raw_timeout!r}") from exc
59
+
if timeout_sec <= 0:
60
+
raise ValueError(f"timeout_sec must be > 0, got {raw_timeout!r}")
61
+
62
+
return model_version, device, timeout_sec, precision
63
+
64
+
65
+
def _resolve_device(device: str, torch_module: Any) -> str:
66
+
"""Resolve auto device selection."""
67
+
if device == "auto":
68
+
return "cuda" if torch_module.cuda.is_available() else "cpu"
69
+
if device == "cuda" and not torch_module.cuda.is_available():
70
+
raise RuntimeError(
71
+
"Parakeet NeMo requested device=cuda but CUDA is unavailable"
72
+
)
73
+
return device
74
+
75
+
76
+
def _resolve_precision(precision: str, resolved_device: str) -> str:
77
+
"""Resolve auto precision selection."""
78
+
if precision == "auto":
79
+
return "float16" if resolved_device == "cuda" else "float32"
80
+
if precision == "float16" and resolved_device != "cuda":
81
+
raise ValueError("precision=float16 requires device=cuda")
82
+
return precision
83
+
84
+
85
+
def _get_model(config: dict) -> tuple[Any, str, str]:
86
+
"""Load or reuse a cached NeMo model."""
87
+
model_version, device, _timeout_sec, precision = _validate_config(config)
88
+
89
+
import torch
90
+
from nemo.collections.asr.models import ASRModel
91
+
92
+
resolved_device = _resolve_device(device, torch)
93
+
resolved_precision = _resolve_precision(precision, resolved_device)
94
+
cache_key = (model_version, resolved_device, resolved_precision)
95
+
if cache_key in _MODEL_CACHE:
96
+
return _MODEL_CACHE[cache_key], resolved_device, resolved_precision
97
+
98
+
try:
99
+
model = ASRModel.from_pretrained(_MODEL_IDS[model_version])
100
+
except Exception as exc:
101
+
raise RuntimeError(f"Parakeet NeMo model download failed: {exc}") from exc
102
+
103
+
model = model.to(resolved_device)
104
+
model = model.half() if resolved_precision == "float16" else model.float()
105
+
model.freeze()
106
+
_MODEL_CACHE[cache_key] = model
107
+
return model, resolved_device, resolved_precision
108
+
109
+
110
+
def _hypothesis_text(hypothesis: Any) -> str:
111
+
"""Extract transcript text from a NeMo hypothesis."""
112
+
if hasattr(hypothesis, "text"):
113
+
return str(hypothesis.text).strip()
114
+
if isinstance(hypothesis, dict):
115
+
return str(hypothesis.get("text", "")).strip()
116
+
return ""
117
+
118
+
119
+
def _word_timestamps(hypothesis: Any) -> list[dict]:
120
+
"""Extract word timestamps from a NeMo hypothesis."""
121
+
timestamp = getattr(hypothesis, "timestamp", None)
122
+
if isinstance(timestamp, dict):
123
+
words = timestamp.get("word", [])
124
+
return words if isinstance(words, list) else []
125
+
126
+
if isinstance(hypothesis, dict):
127
+
timestamp = hypothesis.get("timestamp", {})
128
+
if isinstance(timestamp, dict):
129
+
words = timestamp.get("word", [])
130
+
return words if isinstance(words, list) else []
131
+
132
+
return []
133
+
134
+
135
+
def transcribe(audio: np.ndarray, sample_rate: int, config: dict) -> list[dict]:
136
+
"""Transcribe audio using NeMo Parakeet."""
137
+
model_version, _device, _timeout_sec, _precision = _validate_config(config)
138
+
model, resolved_device, _resolved_precision = _get_model(config)
139
+
140
+
temp_path = None
141
+
started = time.perf_counter()
142
+
try:
143
+
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as handle:
144
+
temp_path = Path(handle.name)
145
+
146
+
audio_int16 = (np.clip(audio, -1.0, 1.0) * 32767).astype(np.int16)
147
+
sf.write(temp_path, audio_int16, sample_rate, format="WAV", subtype="PCM_16")
148
+
149
+
hypotheses = model.transcribe([str(temp_path)], timestamps=True)
150
+
if not hypotheses:
151
+
logging.debug("Parakeet NeMo returned no hypotheses")
152
+
return []
153
+
154
+
hypothesis = hypotheses[0]
155
+
transcript_text = _hypothesis_text(hypothesis)
156
+
raw_words = _word_timestamps(hypothesis)
157
+
if not raw_words:
158
+
logging.debug("Parakeet NeMo returned empty transcript timestamps")
159
+
return []
160
+
161
+
words = []
162
+
for raw_word in raw_words:
163
+
word_text = str(raw_word.get("word", "")).strip()
164
+
if not word_text:
165
+
continue
166
+
word_text = (
167
+
f" {word_text.lstrip()}" # leading space required by build_statement()
168
+
)
169
+
words.append(
170
+
{
171
+
"word": word_text,
172
+
"start": float(raw_word["start"]),
173
+
"end": float(raw_word["end"]),
174
+
"probability": 1.0,
175
+
}
176
+
)
177
+
178
+
if not words:
179
+
logging.debug("Parakeet NeMo word timestamps collapsed to empty output")
180
+
return []
181
+
182
+
acoustic_segments = [
183
+
{
184
+
"id": 1,
185
+
"start": words[0]["start"],
186
+
"end": words[-1]["end"],
187
+
"text": transcript_text,
188
+
"words": words,
189
+
}
190
+
]
191
+
statements = build_statements_from_acoustic(acoustic_segments)
192
+
for statement in statements:
193
+
statement["speaker"] = None
194
+
195
+
elapsed = time.perf_counter() - started
196
+
audio_sec = words[-1]["end"] if words else len(audio) / sample_rate
197
+
rtfx = audio_sec / max(elapsed, 0.001)
198
+
logging.info(
199
+
f" Transcribed {len(statements)} statements, {audio_sec:.2f}s speech "
200
+
f"in {elapsed:.2f}s (RTFx: {rtfx:.2f}) "
201
+
f"[model={model_version} device={resolved_device}]"
202
+
)
203
+
return statements
204
+
finally:
205
+
if temp_path and temp_path.exists():
206
+
temp_path.unlink()
207
+
208
+
209
+
def get_model_info(config: dict) -> dict:
210
+
"""Return NeMo model metadata for transcript JSONL headers."""
211
+
model_version, device, _timeout_sec, precision = _validate_config(config)
212
+
213
+
import torch
214
+
215
+
resolved_device = _resolve_device(device, torch)
216
+
resolved_precision = _resolve_precision(precision, resolved_device)
217
+
return {
218
+
"model": _MODEL_IDS[model_version],
219
+
"device": resolved_device,
220
+
"compute_type": resolved_precision,
221
+
"per_word_confidence": False,
222
+
}
+1
-1
observe/transcribe/main.py
+1
-1
observe/transcribe/main.py
···
799
799
backend_config = {
800
800
k: v
801
801
for k, v in parakeet_config.items()
802
-
if k in ("model_version", "cache_dir", "timeout_sec")
802
+
if k in ("model_version", "cache_dir", "timeout_sec", "device", "precision")
803
803
}
804
804
elif backend == "gemini":
805
805
# Gemini backend - model resolved by think.models based on context
+35
-354
observe/transcribe/parakeet.py
+35
-354
observe/transcribe/parakeet.py
···
1
1
# SPDX-License-Identifier: AGPL-3.0-only
2
2
# Copyright (c) 2026 sol pbc
3
3
4
-
"""Parakeet STT backend via a Swift helper.
4
+
"""Parakeet backend dispatcher.
5
+
6
+
Routes to platform-specific implementations:
7
+
- Apple Silicon (darwin/arm64) -> _parakeet_coreml (FluidAudio helper)
8
+
- Linux x86_64 -> _parakeet_nemo (NeMo + torch)
5
9
6
-
This backend shells out to `observe/transcribe/parakeet_helper/` for FluidAudio
7
-
inference, then rebuilds repo-standard statements with
8
-
`observe.transcribe.utils.build_statements_from_acoustic`.
10
+
Unsupported platforms raise RuntimeError with the detected platform
11
+
and the supported-platforms list.
9
12
"""
10
13
11
14
from __future__ import annotations
12
15
13
-
import difflib
14
-
import json
15
-
import logging
16
-
import os
17
-
import string
18
-
import subprocess
19
-
import tempfile
20
-
from pathlib import Path
16
+
import platform
17
+
import sys
21
18
22
19
import numpy as np
23
-
import soundfile as sf
24
20
25
-
from observe.transcribe.utils import build_statements_from_acoustic
21
+
from . import _parakeet_coreml, _parakeet_nemo
26
22
27
-
_VERSION_CACHE: dict[str, dict] = {}
28
-
_DEFAULT_MODEL_VERSION = "v3"
29
-
_DEFAULT_TIMEOUT_SEC = 120.0
30
-
_DEFAULT_CACHE_DIR = (
31
-
Path.home() / "Library/Application Support/solstone/parakeet/models"
32
-
)
33
-
_VALID_MODEL_VERSIONS = frozenset({"v2", "v3"})
34
-
_PUNCTUATION_TOKENS = frozenset(string.punctuation) | frozenset(
35
-
{"—", "…", "’", "‘", "“", "”"}
36
-
)
37
-
_HELPER_ENV_KEY = "SOLSTONE_PARAKEET_HELPER"
38
23
24
+
def _current_platform() -> tuple[str, str]:
25
+
"""Return normalized platform identifiers for dispatch."""
26
+
os_name = "linux" if sys.platform.startswith("linux") else sys.platform
27
+
return os_name, platform.machine().lower()
39
28
40
-
def transcribe(
41
-
audio: np.ndarray,
42
-
sample_rate: int,
43
-
config: dict,
44
-
) -> list[dict]:
45
-
"""Transcribe audio by invoking the Parakeet helper and rebuilding statements."""
46
-
model_version, cache_dir, timeout_sec = _validate_config(config)
47
-
helper_path = _resolve_helper_path()
48
-
model_info = get_model_info(config)
49
29
50
-
temp_path = None
51
-
try:
52
-
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as handle:
53
-
temp_path = Path(handle.name)
30
+
def _unsupported_platform_message(os_name: str, arch: str) -> str:
31
+
"""Build the unsupported-platform error message."""
32
+
return (
33
+
f"Unsupported Parakeet platform: {os_name}/{arch}. "
34
+
"Supported platforms: darwin/arm64, linux/x86_64"
35
+
)
54
36
55
-
audio_int16 = (np.clip(audio, -1.0, 1.0) * 32767).astype(np.int16)
56
-
sf.write(temp_path, audio_int16, sample_rate, format="WAV", subtype="PCM_16")
57
37
58
-
argv = [
59
-
str(helper_path),
60
-
"--cache-dir",
61
-
str(cache_dir),
62
-
"--model",
63
-
model_version,
64
-
str(temp_path),
65
-
]
66
-
67
-
try:
68
-
result = subprocess.run(
69
-
argv,
70
-
check=False,
71
-
capture_output=True,
72
-
text=True,
73
-
timeout=timeout_sec,
74
-
)
75
-
except subprocess.TimeoutExpired as exc:
76
-
raise RuntimeError(
77
-
f"Parakeet helper timed out after {timeout_sec:.1f}s. Rebuild with "
78
-
f"'make parakeet-helper', increase transcribe.parakeet.timeout_sec, "
79
-
f"or set ${_HELPER_ENV_KEY} to a different helper build."
80
-
) from exc
81
-
82
-
if result.returncode != 0:
83
-
stderr = (result.stderr or "").strip()
84
-
try:
85
-
stderr_json = json.loads(stderr) if stderr else {}
86
-
except json.JSONDecodeError:
87
-
stderr_json = {}
88
-
message = stderr_json.get("message") or stderr or "unknown helper failure"
89
-
90
-
if result.returncode == 2:
91
-
raise RuntimeError(
92
-
f"Parakeet helper rejected validated arguments (internal bug — file an issue): {message}"
93
-
)
94
-
if result.returncode == 3:
95
-
raise RuntimeError(
96
-
f"Parakeet helper could not prepare cache dir {cache_dir}: {message}"
97
-
)
98
-
if result.returncode == 4:
99
-
raise RuntimeError(
100
-
f"Parakeet helper failed to download or load model '{model_version}'. "
101
-
f"Valid values: v2, v3. {message}"
102
-
)
103
-
if result.returncode == 5:
104
-
raise RuntimeError(
105
-
f"Parakeet helper failed to transcribe audio: {message}"
106
-
)
107
-
raise RuntimeError(
108
-
f"Parakeet helper failed with exit code {result.returncode}: {message}"
109
-
)
110
-
111
-
try:
112
-
payload = json.loads(result.stdout)
113
-
except json.JSONDecodeError as exc:
114
-
raise RuntimeError(f"Parakeet helper returned invalid JSON: {exc}") from exc
115
-
if not isinstance(payload, dict):
116
-
raise RuntimeError("Parakeet helper returned a non-object JSON payload")
117
-
118
-
helper_transcript = str(payload.get("transcript", "")).strip()
119
-
token_timings = payload.get("token_timings", [])
120
-
if not token_timings:
121
-
if helper_transcript:
122
-
raise RuntimeError(
123
-
"Parakeet helper returned transcript text without token timings "
124
-
"(internal bug — file an issue)."
125
-
)
126
-
return []
127
-
128
-
words = _collapse_subwords_to_words(token_timings)
129
-
if not words:
130
-
if helper_transcript:
131
-
raise RuntimeError(
132
-
"Parakeet helper returned token timings that collapsed to no words "
133
-
"(internal bug — file an issue)."
134
-
)
135
-
return []
136
-
137
-
acoustic_segments = [
138
-
{
139
-
"id": 1,
140
-
"start": words[0]["start"],
141
-
"end": words[-1]["end"],
142
-
"text": helper_transcript,
143
-
"words": words,
144
-
}
145
-
]
146
-
statements = build_statements_from_acoustic(acoustic_segments)
147
-
for statement in statements:
148
-
statement["speaker"] = None
149
-
150
-
rebuilt_text = " ".join(statement["text"] for statement in statements).strip()
151
-
_log_drift_if_needed(helper_transcript, rebuilt_text)
152
-
153
-
audio_sec = float(payload.get("audio_sec", len(audio) / sample_rate))
154
-
transcribe_ms = int(payload.get("transcribe_ms", 0))
155
-
tx_sec = transcribe_ms / 1000.0
156
-
rtfx = float(payload.get("rtfx", 0.0))
157
-
logging.info(
158
-
f" Transcribed {len(statements)} statements, {audio_sec:.2f}s speech "
159
-
f"in {tx_sec:.2f}s (RTFx: {rtfx:.2f}) [model={model_info['model']}]"
160
-
)
161
-
162
-
return statements
163
-
164
-
finally:
165
-
if temp_path and temp_path.exists():
166
-
temp_path.unlink()
38
+
def transcribe(audio: np.ndarray, sample_rate: int, config: dict) -> list[dict]:
39
+
"""Dispatch Parakeet transcription to the platform-specific backend."""
40
+
os_name, arch = _current_platform()
41
+
if os_name == "darwin" and arch == "arm64":
42
+
return _parakeet_coreml.transcribe(audio, sample_rate, config)
43
+
if os_name == "linux" and arch == "x86_64":
44
+
return _parakeet_nemo.transcribe(audio, sample_rate, config)
45
+
raise RuntimeError(_unsupported_platform_message(os_name, arch))
167
46
168
47
169
48
def get_model_info(config: dict) -> dict:
170
-
"""Return Parakeet model metadata for transcript JSONL headers."""
171
-
model_version, _cache_dir, _timeout_sec = _validate_config(config)
172
-
helper_path = _resolve_helper_path()
173
-
version_envelope = _probe_helper_version(helper_path)
174
-
return {
175
-
"model": f"parakeet-tdt-0.6b-{model_version}",
176
-
"device": "ane",
177
-
"compute_type": "coreml_fp16",
178
-
"fluidaudio_version": version_envelope["fluidaudio_version"],
179
-
"helper_hardware": version_envelope["hardware"],
180
-
}
181
-
182
-
183
-
def _resolve_helper_path() -> Path:
184
-
"""Resolve the Parakeet helper path from env override or default build path."""
185
-
env_path = os.getenv(_HELPER_ENV_KEY)
186
-
if env_path:
187
-
candidate = Path(env_path).expanduser().resolve()
188
-
if not candidate.exists():
189
-
raise RuntimeError(
190
-
f"Parakeet helper not found at ${_HELPER_ENV_KEY}={candidate}. "
191
-
f"Run 'make parakeet-helper' or point ${_HELPER_ENV_KEY} at a valid executable."
192
-
)
193
-
if not candidate.is_file() or not os.access(candidate, os.X_OK):
194
-
raise RuntimeError(
195
-
f"Parakeet helper at ${_HELPER_ENV_KEY}={candidate} is not executable. "
196
-
f"Run 'make parakeet-helper', chmod +x the file, or point "
197
-
f"${_HELPER_ENV_KEY} at a valid executable."
198
-
)
199
-
return candidate
200
-
201
-
candidate = (
202
-
Path(__file__).with_name("parakeet_helper")
203
-
/ ".build"
204
-
/ "release"
205
-
/ "parakeet-helper"
206
-
).resolve()
207
-
if (
208
-
not candidate.exists()
209
-
or not candidate.is_file()
210
-
or not os.access(candidate, os.X_OK)
211
-
):
212
-
raise RuntimeError(
213
-
f"Parakeet helper not found at {candidate}. Run 'make parakeet-helper' "
214
-
f"or set ${_HELPER_ENV_KEY} to a valid executable."
215
-
)
216
-
return candidate
217
-
218
-
219
-
def _probe_helper_version(helper_path: Path) -> dict:
220
-
"""Probe and cache the helper version envelope by resolved binary path."""
221
-
cache_key = str(helper_path.resolve())
222
-
if cache_key in _VERSION_CACHE:
223
-
return _VERSION_CACHE[cache_key]
224
-
225
-
try:
226
-
result = subprocess.run(
227
-
[str(helper_path), "--version"],
228
-
check=False,
229
-
capture_output=True,
230
-
text=True,
231
-
timeout=10.0,
232
-
)
233
-
except subprocess.TimeoutExpired as exc:
234
-
raise RuntimeError(
235
-
f"Parakeet helper timed out after 10.0s. Rebuild with "
236
-
f"'make parakeet-helper', increase transcribe.parakeet.timeout_sec, "
237
-
f"or set ${_HELPER_ENV_KEY} to a different helper build."
238
-
) from exc
239
-
240
-
if result.returncode != 0:
241
-
stderr = (result.stderr or "").strip()
242
-
try:
243
-
stderr_json = json.loads(stderr) if stderr else {}
244
-
except json.JSONDecodeError:
245
-
stderr_json = {}
246
-
message = stderr_json.get("message") or stderr or "unknown helper failure"
247
-
if result.returncode == 2:
248
-
raise RuntimeError(
249
-
f"Parakeet helper rejected validated arguments (internal bug — file an issue): {message}"
250
-
)
251
-
if result.returncode == 3:
252
-
raise RuntimeError(
253
-
f"Parakeet helper could not prepare cache dir {_DEFAULT_CACHE_DIR}: {message}"
254
-
)
255
-
if result.returncode == 4:
256
-
raise RuntimeError(
257
-
f"Parakeet helper failed to download or load model '{_DEFAULT_MODEL_VERSION}'. "
258
-
f"Valid values: v2, v3. {message}"
259
-
)
260
-
if result.returncode == 5:
261
-
raise RuntimeError(f"Parakeet helper failed to transcribe audio: {message}")
262
-
raise RuntimeError(
263
-
f"Parakeet helper failed with exit code {result.returncode}: {message}"
264
-
)
265
-
266
-
try:
267
-
payload = json.loads(result.stdout)
268
-
except json.JSONDecodeError as exc:
269
-
raise RuntimeError(
270
-
f"Parakeet helper returned invalid version JSON: {exc}"
271
-
) from exc
272
-
if not isinstance(payload, dict):
273
-
raise RuntimeError("Parakeet helper returned a non-object version payload")
274
-
275
-
_VERSION_CACHE[cache_key] = payload
276
-
return payload
277
-
278
-
279
-
def _collapse_subwords_to_words(token_timings: list[dict]) -> list[dict]:
280
-
"""Collapse helper token timings into repo-standard word dicts."""
281
-
if not token_timings:
282
-
return []
283
-
284
-
words = []
285
-
current_parts: list[str] = []
286
-
current_confidences: list[float] = []
287
-
current_start: float | None = None
288
-
current_end: float | None = None
289
-
290
-
def flush() -> None:
291
-
nonlocal current_parts, current_confidences, current_start, current_end
292
-
if not current_parts or current_start is None or current_end is None:
293
-
current_parts = []
294
-
current_confidences = []
295
-
current_start = None
296
-
current_end = None
297
-
return
298
-
text = "".join(current_parts).lstrip()
299
-
words.append(
300
-
{
301
-
"word": f" {text}",
302
-
"start": current_start,
303
-
"end": current_end,
304
-
"probability": min(current_confidences),
305
-
}
306
-
)
307
-
current_parts = []
308
-
current_confidences = []
309
-
current_start = None
310
-
current_end = None
311
-
312
-
for token in token_timings:
313
-
raw = str(token.get("token", ""))
314
-
is_punctuation = bool(raw) and all(
315
-
char in _PUNCTUATION_TOKENS for char in raw if char
316
-
)
317
-
starts_new = raw.startswith("▁") or raw.startswith(" ")
318
-
319
-
if starts_new and current_parts and not is_punctuation:
320
-
flush()
321
-
322
-
cleaned = raw.lstrip("▁")
323
-
if starts_new:
324
-
cleaned = cleaned.lstrip(" ")
325
-
326
-
current_parts.append(cleaned)
327
-
current_confidences.append(float(token.get("confidence", 0.0)))
328
-
329
-
if not is_punctuation and current_start is None:
330
-
current_start = float(token["start"])
331
-
if not is_punctuation:
332
-
current_end = float(token["end"])
333
-
334
-
flush()
335
-
return words
336
-
337
-
338
-
def _log_drift_if_needed(fluid_transcript: str, rebuilt_text: str) -> None:
339
-
"""Warn when helper text and rebuilt text materially diverge."""
340
-
fluid_transcript = fluid_transcript.strip()
341
-
rebuilt_text = rebuilt_text.strip()
342
-
if not fluid_transcript or not rebuilt_text:
343
-
return
344
-
345
-
ratio = difflib.SequenceMatcher(None, fluid_transcript, rebuilt_text).ratio()
346
-
if ratio < 0.95:
347
-
logging.warning(
348
-
"Parakeet transcript drift detected (ratio=%.3f): helper=%r rebuilt=%r",
349
-
ratio,
350
-
fluid_transcript,
351
-
rebuilt_text,
352
-
)
353
-
354
-
355
-
def _validate_config(config: dict) -> tuple[str, Path, float]:
356
-
"""Validate backend config before spawning the helper."""
357
-
model_version = config.get("model_version", _DEFAULT_MODEL_VERSION)
358
-
if model_version not in _VALID_MODEL_VERSIONS:
359
-
raise ValueError("model_version must be one of: v2, v3")
360
-
361
-
raw_timeout = config.get("timeout_sec", _DEFAULT_TIMEOUT_SEC)
362
-
try:
363
-
timeout_sec = float(raw_timeout)
364
-
except (TypeError, ValueError) as exc:
365
-
raise ValueError(f"timeout_sec must be > 0, got {raw_timeout!r}") from exc
366
-
if timeout_sec <= 0:
367
-
raise ValueError(f"timeout_sec must be > 0, got {raw_timeout!r}")
368
-
369
-
raw_cache_dir = config.get("cache_dir")
370
-
cache_dir = (
371
-
Path(raw_cache_dir).expanduser() if raw_cache_dir else _DEFAULT_CACHE_DIR
372
-
)
373
-
374
-
return model_version, cache_dir, timeout_sec
49
+
"""Dispatch Parakeet model-info lookup to the platform-specific backend."""
50
+
os_name, arch = _current_platform()
51
+
if os_name == "darwin" and arch == "arm64":
52
+
return _parakeet_coreml.get_model_info(config)
53
+
if os_name == "linux" and arch == "x86_64":
54
+
return _parakeet_nemo.get_model_info(config)
55
+
raise RuntimeError(_unsupported_platform_message(os_name, arch))
+6
pyproject.toml
+6
pyproject.toml
+3
-2
tests/baselines/api/settings/transcribe.json
+3
-2
tests/baselines/api/settings/transcribe.json
···
34
34
]
35
35
},
36
36
{
37
-
"description": "On-device speech recognition via FluidAudio + Parakeet TDT; requires `make parakeet-helper`",
37
+
"description": "On-device speech recognition via Parakeet TDT; macOS uses a FluidAudio/CoreML helper, Linux uses NeMo + torch. Requires `make install`.",
38
38
"env_key": null,
39
-
"label": "Parakeet - Local processing (Apple Silicon, optional helper)",
39
+
"label": "Parakeet - Local processing (Apple Silicon CoreML or Linux NeMo)",
40
40
"name": "parakeet",
41
41
"settings": [
42
42
"model_version",
43
+
"device",
43
44
"timeout_sec"
44
45
]
45
46
}
+11
tests/conftest.py
+11
tests/conftest.py
···
172
172
sklearn = types.ModuleType("sklearn")
173
173
sklearn.metrics = metrics
174
174
sklearn.cluster = cluster
175
+
sklearn.__spec__ = importlib.machinery.ModuleSpec("sklearn", loader=None)
176
+
metrics.__spec__ = importlib.machinery.ModuleSpec(
177
+
"sklearn.metrics", loader=None
178
+
)
179
+
pairwise.__spec__ = importlib.machinery.ModuleSpec(
180
+
"sklearn.metrics.pairwise", loader=None
181
+
)
182
+
cluster.__spec__ = importlib.machinery.ModuleSpec(
183
+
"sklearn.cluster", loader=None
184
+
)
175
185
sys.modules["sklearn"] = sklearn
176
186
sys.modules["sklearn.metrics"] = metrics
177
187
sys.modules["sklearn.metrics.pairwise"] = pairwise
···
287
297
sys.modules["google.genai"] = genai_mod
288
298
if "cv2" not in sys.modules:
289
299
cv2_mod = types.ModuleType("cv2")
300
+
cv2_mod.__spec__ = importlib.machinery.ModuleSpec("cv2", loader=None)
290
301
cv2_mod.COLOR_RGB2LAB = 0
291
302
292
303
def cvtColor(arr, code):
+1
-1
tests/test_transcribe_parakeet.py
tests/test_transcribe_parakeet_coreml.py
+1
-1
tests/test_transcribe_parakeet.py
tests/test_transcribe_parakeet_coreml.py
+84
tests/test_transcribe_parakeet_dispatch.py
+84
tests/test_transcribe_parakeet_dispatch.py
···
1
+
# SPDX-License-Identifier: AGPL-3.0-only
2
+
# Copyright (c) 2026 sol pbc
3
+
4
+
import platform
5
+
import sys
6
+
7
+
import pytest
8
+
9
+
import observe.transcribe.parakeet as parakeet
10
+
11
+
12
+
def test_nemo_module_imports_without_nemo_installed():
13
+
import observe.transcribe._parakeet_nemo # noqa: F401
14
+
15
+
16
+
def test_dispatch_transcribe_routes_darwin_arm64(monkeypatch: pytest.MonkeyPatch):
17
+
monkeypatch.setattr(sys, "platform", "darwin")
18
+
monkeypatch.setattr(platform, "machine", lambda: "arm64")
19
+
monkeypatch.setattr(
20
+
parakeet._parakeet_coreml,
21
+
"transcribe",
22
+
lambda *args, **kwargs: [{"arm": "coreml"}],
23
+
)
24
+
monkeypatch.setattr(
25
+
parakeet._parakeet_nemo, "transcribe", lambda *args, **kwargs: [{"arm": "nemo"}]
26
+
)
27
+
28
+
assert parakeet.transcribe([], 16000, {}) == [{"arm": "coreml"}]
29
+
30
+
31
+
def test_dispatch_transcribe_routes_linux_x86_64(monkeypatch: pytest.MonkeyPatch):
32
+
monkeypatch.setattr(sys, "platform", "linux")
33
+
monkeypatch.setattr(platform, "machine", lambda: "x86_64")
34
+
monkeypatch.setattr(
35
+
parakeet._parakeet_coreml,
36
+
"transcribe",
37
+
lambda *args, **kwargs: [{"arm": "coreml"}],
38
+
)
39
+
monkeypatch.setattr(
40
+
parakeet._parakeet_nemo, "transcribe", lambda *args, **kwargs: [{"arm": "nemo"}]
41
+
)
42
+
43
+
assert parakeet.transcribe([], 16000, {}) == [{"arm": "nemo"}]
44
+
45
+
46
+
@pytest.mark.parametrize(
47
+
("os_name", "arch", "expected"),
48
+
[
49
+
("darwin", "x86_64", "darwin/x86_64"),
50
+
("linux", "aarch64", "linux/aarch64"),
51
+
("win32", "AMD64", "win32/amd64"),
52
+
],
53
+
)
54
+
def test_dispatch_transcribe_unsupported_platforms_raise(
55
+
monkeypatch: pytest.MonkeyPatch,
56
+
os_name: str,
57
+
arch: str,
58
+
expected: str,
59
+
):
60
+
monkeypatch.setattr(sys, "platform", os_name)
61
+
monkeypatch.setattr(platform, "machine", lambda: arch)
62
+
63
+
with pytest.raises(RuntimeError, match="Supported platforms"):
64
+
parakeet.transcribe([], 16000, {})
65
+
66
+
with pytest.raises(RuntimeError) as exc_info:
67
+
parakeet.transcribe([], 16000, {})
68
+
69
+
message = str(exc_info.value)
70
+
assert expected in message
71
+
assert "darwin/arm64" in message
72
+
assert "linux/x86_64" in message
73
+
74
+
75
+
def test_dispatch_get_model_info_routes_linux_x86_64(
76
+
monkeypatch: pytest.MonkeyPatch,
77
+
):
78
+
monkeypatch.setattr(sys, "platform", "linux")
79
+
monkeypatch.setattr(platform, "machine", lambda: "x86_64")
80
+
monkeypatch.setattr(
81
+
parakeet._parakeet_nemo, "get_model_info", lambda config: {"arm": "nemo"}
82
+
)
83
+
84
+
assert parakeet.get_model_info({}) == {"arm": "nemo"}
+75
tests/test_transcribe_parakeet_nemo.py
+75
tests/test_transcribe_parakeet_nemo.py
···
1
+
# SPDX-License-Identifier: AGPL-3.0-only
2
+
# Copyright (c) 2026 sol pbc
3
+
4
+
import platform
5
+
from pathlib import Path
6
+
7
+
import pytest
8
+
import soundfile as sf
9
+
10
+
if platform.system() != "Linux":
11
+
pytest.skip("Linux-only NeMo test", allow_module_level=True)
12
+
13
+
try:
14
+
import google.protobuf.json_format # noqa: F401
15
+
import sklearn.metrics.pairwise # noqa: F401 # real sklearn preempts conftest stub
16
+
except ImportError:
17
+
pass
18
+
19
+
import observe.transcribe._parakeet_nemo as parakeet_nemo
20
+
21
+
22
+
def _require_nemo() -> None:
23
+
try:
24
+
import nemo # noqa: F401
25
+
except ImportError:
26
+
pytest.skip("NeMo not installed")
27
+
28
+
29
+
@pytest.fixture
30
+
def pangram_audio() -> tuple[object, int]:
31
+
fixture_path = Path("tests/fixtures/parakeet_sample.wav")
32
+
return sf.read(fixture_path, dtype="float32")
33
+
34
+
35
+
@pytest.mark.timeout(120)
36
+
def test_transcribe_nemo_pangram(pangram_audio: tuple[object, int]):
37
+
_require_nemo()
38
+
audio, sample_rate = pangram_audio
39
+
40
+
statements = parakeet_nemo.transcribe(audio, sample_rate, {"device": "cpu"})
41
+
42
+
assert statements
43
+
combined_text = " ".join(statement["text"] for statement in statements).lower()
44
+
assert "quick" in combined_text
45
+
assert "fox" in combined_text
46
+
for statement in statements:
47
+
assert all(
48
+
word["word"].startswith(" ") and not word["word"].startswith(" ")
49
+
for word in statement["words"]
50
+
)
51
+
52
+
53
+
def test_get_model_info_shape():
54
+
_require_nemo()
55
+
56
+
info = parakeet_nemo.get_model_info({"device": "cpu"})
57
+
58
+
assert {"model", "device", "compute_type", "per_word_confidence"} <= set(info)
59
+
assert info["per_word_confidence"] is False
60
+
61
+
62
+
def test_invalid_device_raises(pangram_audio: tuple[object, int]):
63
+
_require_nemo()
64
+
audio, sample_rate = pangram_audio
65
+
66
+
with pytest.raises(ValueError, match="auto, cpu, cuda"):
67
+
parakeet_nemo.transcribe(audio, sample_rate, {"device": "tpu"})
68
+
69
+
70
+
def test_unsupported_model_version_raises(pangram_audio: tuple[object, int]):
71
+
_require_nemo()
72
+
audio, sample_rate = pangram_audio
73
+
74
+
with pytest.raises(ValueError, match="v2, v3"):
75
+
parakeet_nemo.transcribe(audio, sample_rate, {"model_version": "v9"})
+4429
-48
uv.lock
+4429
-48
uv.lock
···
2
2
revision = 3
3
3
requires-python = ">=3.10"
4
4
resolution-markers = [
5
-
"python_full_version >= '3.13'",
6
-
"python_full_version == '3.12.*'",
7
-
"python_full_version == '3.11.*'",
8
-
"python_full_version < '3.11'",
5
+
"python_full_version >= '3.14' and platform_machine != 's390x' and sys_platform == 'win32'",
6
+
"python_full_version >= '3.14' and platform_machine != 's390x' and sys_platform == 'emscripten'",
7
+
"python_full_version >= '3.14' and platform_machine != 's390x' and sys_platform != 'emscripten' and sys_platform != 'win32'",
8
+
"python_full_version == '3.13.*' and platform_machine != 's390x' and sys_platform == 'win32'",
9
+
"python_full_version == '3.13.*' and platform_machine != 's390x' and sys_platform == 'emscripten'",
10
+
"python_full_version == '3.13.*' and platform_machine != 's390x' and sys_platform != 'emscripten' and sys_platform != 'win32'",
11
+
"python_full_version >= '3.14' and platform_machine == 's390x' and sys_platform == 'win32'",
12
+
"python_full_version >= '3.14' and platform_machine == 's390x' and sys_platform == 'emscripten'",
13
+
"python_full_version >= '3.14' and platform_machine == 's390x' and sys_platform != 'emscripten' and sys_platform != 'win32'",
14
+
"python_full_version == '3.13.*' and platform_machine == 's390x' and sys_platform == 'win32'",
15
+
"python_full_version == '3.13.*' and platform_machine == 's390x' and sys_platform == 'emscripten'",
16
+
"python_full_version == '3.13.*' and platform_machine == 's390x' and sys_platform != 'emscripten' and sys_platform != 'win32'",
17
+
"python_full_version == '3.12.*' and platform_machine != 's390x' and sys_platform == 'win32'",
18
+
"python_full_version == '3.12.*' and platform_machine != 's390x' and sys_platform == 'emscripten'",
19
+
"python_full_version == '3.12.*' and platform_machine != 's390x' and sys_platform != 'emscripten' and sys_platform != 'win32'",
20
+
"python_full_version == '3.12.*' and platform_machine == 's390x' and sys_platform == 'win32'",
21
+
"python_full_version == '3.12.*' and platform_machine == 's390x' and sys_platform == 'emscripten'",
22
+
"python_full_version == '3.12.*' and platform_machine == 's390x' and sys_platform != 'emscripten' and sys_platform != 'win32'",
23
+
"python_full_version == '3.11.*' and platform_machine != 's390x' and sys_platform == 'win32'",
24
+
"python_full_version == '3.11.*' and platform_machine != 's390x' and sys_platform == 'emscripten'",
25
+
"python_full_version == '3.11.*' and platform_machine != 's390x' and sys_platform != 'emscripten' and sys_platform != 'win32'",
26
+
"python_full_version == '3.11.*' and platform_machine == 's390x' and sys_platform == 'win32'",
27
+
"python_full_version == '3.11.*' and platform_machine == 's390x' and sys_platform == 'emscripten'",
28
+
"python_full_version == '3.11.*' and platform_machine == 's390x' and sys_platform != 'emscripten' and sys_platform != 'win32'",
29
+
"python_full_version < '3.11' and platform_machine != 's390x'",
30
+
"python_full_version < '3.11' and platform_machine == 's390x'",
31
+
]
32
+
33
+
[[package]]
34
+
name = "absl-py"
35
+
version = "2.4.0"
36
+
source = { registry = "https://pypi.org/simple" }
37
+
sdist = { url = "https://files.pythonhosted.org/packages/64/c7/8de93764ad66968d19329a7e0c147a2bb3c7054c554d4a119111b8f9440f/absl_py-2.4.0.tar.gz", hash = "sha256:8c6af82722b35cf71e0f4d1d47dcaebfff286e27110a99fc359349b247dfb5d4", size = 116543, upload-time = "2026-01-28T10:17:05.322Z" }
38
+
wheels = [
39
+
{ url = "https://files.pythonhosted.org/packages/18/a6/907a406bb7d359e6a63f99c313846d9eec4f7e6f7437809e03aa00fa3074/absl_py-2.4.0-py3-none-any.whl", hash = "sha256:88476fd881ca8aab94ffa78b7b6c632a782ab3ba1cd19c9bd423abc4fb4cd28d", size = 135750, upload-time = "2026-01-28T10:17:04.19Z" },
40
+
]
41
+
42
+
[[package]]
43
+
name = "accelerate"
44
+
version = "1.13.0"
45
+
source = { registry = "https://pypi.org/simple" }
46
+
dependencies = [
47
+
{ name = "huggingface-hub" },
48
+
{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
49
+
{ name = "numpy", version = "2.3.5", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
50
+
{ name = "packaging" },
51
+
{ name = "psutil" },
52
+
{ name = "pyyaml" },
53
+
{ name = "safetensors" },
54
+
{ name = "torch" },
55
+
]
56
+
sdist = { url = "https://files.pythonhosted.org/packages/ca/14/787e5498cd062640f0f3d92ef4ae4063174f76f9afd29d13fc52a319daae/accelerate-1.13.0.tar.gz", hash = "sha256:d631b4e0f5b3de4aff2d7e9e6857d164810dfc3237d54d017f075122d057b236", size = 402835, upload-time = "2026-03-04T19:34:12.359Z" }
57
+
wheels = [
58
+
{ url = "https://files.pythonhosted.org/packages/7e/46/02ac5e262d4af18054b3e922b2baedbb2a03289ee792162de60a865defc5/accelerate-1.13.0-py3-none-any.whl", hash = "sha256:cf1a3efb96c18f7b152eb0fa7490f3710b19c3f395699358f08decca2b8b62e0", size = 383744, upload-time = "2026-03-04T19:34:10.313Z" },
59
+
]
60
+
61
+
[[package]]
62
+
name = "aiohappyeyeballs"
63
+
version = "2.6.1"
64
+
source = { registry = "https://pypi.org/simple" }
65
+
sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760, upload-time = "2025-03-12T01:42:48.764Z" }
66
+
wheels = [
67
+
{ url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265, upload-time = "2025-03-12T01:42:47.083Z" },
68
+
]
69
+
70
+
[[package]]
71
+
name = "aiohttp"
72
+
version = "3.13.5"
73
+
source = { registry = "https://pypi.org/simple" }
74
+
dependencies = [
75
+
{ name = "aiohappyeyeballs" },
76
+
{ name = "aiosignal" },
77
+
{ name = "async-timeout", marker = "python_full_version < '3.11'" },
78
+
{ name = "attrs" },
79
+
{ name = "frozenlist" },
80
+
{ name = "multidict" },
81
+
{ name = "propcache" },
82
+
{ name = "yarl" },
83
+
]
84
+
sdist = { url = "https://files.pythonhosted.org/packages/77/9a/152096d4808df8e4268befa55fba462f440f14beab85e8ad9bf990516918/aiohttp-3.13.5.tar.gz", hash = "sha256:9d98cc980ecc96be6eb4c1994ce35d28d8b1f5e5208a23b421187d1209dbb7d1", size = 7858271, upload-time = "2026-03-31T22:01:03.343Z" }
85
+
wheels = [
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1545
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1576
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1577
748
1578
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1603
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765
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766
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1647
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1649
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1650
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1651
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1652
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1653
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1654
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1655
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1656
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1658
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1659
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1660
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767
1661
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768
1662
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769
1663
source = { registry = "https://pypi.org/simple" }
···
776
1670
]
777
1671
778
1672
[[package]]
1673
+
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1674
+
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1675
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1676
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1677
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1679
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1680
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1681
+
[[package]]
779
1682
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780
1683
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781
1684
source = { registry = "https://pypi.org/simple" }
···
789
1692
]
790
1693
wheels = [
791
1694
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1695
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1696
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1697
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1698
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1699
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1700
+
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1701
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1702
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{ name = "absl-py" },
1703
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{ name = "graphviz" },
1704
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1705
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{ name = "typing-extensions" },
1706
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1707
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1708
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1709
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792
1710
]
793
1711
794
1712
[[package]]
···
920
1838
]
921
1839
922
1840
[[package]]
1841
+
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1842
+
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1843
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1844
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1845
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wheels = [
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1847
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1848
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1849
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1850
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1851
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1852
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1946
+
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1947
+
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1948
+
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1949
+
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1950
+
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1951
+
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1952
+
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1953
+
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1954
+
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1955
+
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1956
+
{ url = "https://files.pythonhosted.org/packages/89/76/c615883b7b521ead2944bb3480398cbb07e12b7b4e4d073d3752eb721558/frozenlist-1.8.0-cp314-cp314t-win_amd64.whl", hash = "sha256:06be8f67f39c8b1dc671f5d83aaefd3358ae5cdcf8314552c57e7ed3e6475bdd", size = 49451, upload-time = "2025-10-06T05:37:53.425Z" },
1957
+
{ url = "https://files.pythonhosted.org/packages/e0/a3/5982da14e113d07b325230f95060e2169f5311b1017ea8af2a29b374c289/frozenlist-1.8.0-cp314-cp314t-win_arm64.whl", hash = "sha256:102e6314ca4da683dca92e3b1355490fed5f313b768500084fbe6371fddfdb79", size = 42507, upload-time = "2025-10-06T05:37:54.513Z" },
1958
+
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1959
+
]
1960
+
1961
+
[[package]]
923
1962
name = "fsspec"
924
-
version = "2026.2.0"
1963
+
version = "2024.12.0"
925
1964
source = { registry = "https://pypi.org/simple" }
926
-
sdist = { url = "https://files.pythonhosted.org/packages/51/7c/f60c259dcbf4f0c47cc4ddb8f7720d2dcdc8888c8e5ad84c73ea4531cc5b/fsspec-2026.2.0.tar.gz", hash = "sha256:6544e34b16869f5aacd5b90bdf1a71acb37792ea3ddf6125ee69a22a53fb8bff", size = 313441, upload-time = "2026-02-05T21:50:53.743Z" }
1965
+
sdist = { url = "https://files.pythonhosted.org/packages/ee/11/de70dee31455c546fbc88301971ec03c328f3d1138cfba14263f651e9551/fsspec-2024.12.0.tar.gz", hash = "sha256:670700c977ed2fb51e0d9f9253177ed20cbde4a3e5c0283cc5385b5870c8533f", size = 291600, upload-time = "2024-12-19T19:57:30.333Z" }
927
1966
wheels = [
928
-
{ url = "https://files.pythonhosted.org/packages/e6/ab/fb21f4c939bb440104cc2b396d3be1d9b7a9fd3c6c2a53d98c45b3d7c954/fsspec-2026.2.0-py3-none-any.whl", hash = "sha256:98de475b5cb3bd66bedd5c4679e87b4fdfe1a3bf4d707b151b3c07e58c9a2437", size = 202505, upload-time = "2026-02-05T21:50:51.819Z" },
1967
+
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1968
+
]
1969
+
1970
+
[package.optional-dependencies]
1971
+
http = [
1972
+
{ name = "aiohttp" },
929
1973
]
930
1974
931
1975
[[package]]
···
942
1986
]
943
1987
944
1988
[[package]]
1989
+
name = "gitdb"
1990
+
version = "4.0.12"
1991
+
source = { registry = "https://pypi.org/simple" }
1992
+
dependencies = [
1993
+
{ name = "smmap" },
1994
+
]
1995
+
sdist = { url = "https://files.pythonhosted.org/packages/72/94/63b0fc47eb32792c7ba1fe1b694daec9a63620db1e313033d18140c2320a/gitdb-4.0.12.tar.gz", hash = "sha256:5ef71f855d191a3326fcfbc0d5da835f26b13fbcba60c32c21091c349ffdb571", size = 394684, upload-time = "2025-01-02T07:20:46.413Z" }
1996
+
wheels = [
1997
+
{ url = "https://files.pythonhosted.org/packages/a0/61/5c78b91c3143ed5c14207f463aecfc8f9dbb5092fb2869baf37c273b2705/gitdb-4.0.12-py3-none-any.whl", hash = "sha256:67073e15955400952c6565cc3e707c554a4eea2e428946f7a4c162fab9bd9bcf", size = 62794, upload-time = "2025-01-02T07:20:43.624Z" },
1998
+
]
1999
+
2000
+
[[package]]
2001
+
name = "gitpython"
2002
+
version = "3.1.47"
2003
+
source = { registry = "https://pypi.org/simple" }
2004
+
dependencies = [
2005
+
{ name = "gitdb" },
2006
+
]
2007
+
sdist = { url = "https://files.pythonhosted.org/packages/c1/bd/50db468e9b1310529a19fce651b3b0e753b5c07954d486cba31bbee9a5d5/gitpython-3.1.47.tar.gz", hash = "sha256:dba27f922bd2b42cb54c87a8ab3cb6beb6bf07f3d564e21ac848913a05a8a3cd", size = 216978, upload-time = "2026-04-22T02:44:44.059Z" }
2008
+
wheels = [
2009
+
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2010
+
]
2011
+
2012
+
[[package]]
945
2013
name = "google-auth"
946
2014
version = "2.48.0"
947
2015
source = { registry = "https://pypi.org/simple" }
···
982
2050
]
983
2051
984
2052
[[package]]
2053
+
name = "graphviz"
2054
+
version = "0.21"
2055
+
source = { registry = "https://pypi.org/simple" }
2056
+
sdist = { url = "https://files.pythonhosted.org/packages/f8/b3/3ac91e9be6b761a4b30d66ff165e54439dcd48b83f4e20d644867215f6ca/graphviz-0.21.tar.gz", hash = "sha256:20743e7183be82aaaa8ad6c93f8893c923bd6658a04c32ee115edb3c8a835f78", size = 200434, upload-time = "2025-06-15T09:35:05.824Z" }
2057
+
wheels = [
2058
+
{ url = "https://files.pythonhosted.org/packages/91/4c/e0ce1ef95d4000ebc1c11801f9b944fa5910ecc15b5e351865763d8657f8/graphviz-0.21-py3-none-any.whl", hash = "sha256:54f33de9f4f911d7e84e4191749cac8cc5653f815b06738c54db9a15ab8b1e42", size = 47300, upload-time = "2025-06-15T09:35:04.433Z" },
2059
+
]
2060
+
2061
+
[[package]]
985
2062
name = "greenlet"
986
2063
version = "3.3.1"
987
2064
source = { registry = "https://pypi.org/simple" }
···
1042
2119
]
1043
2120
1044
2121
[[package]]
2122
+
name = "grpcio"
2123
+
version = "1.80.0"
2124
+
source = { registry = "https://pypi.org/simple" }
2125
+
dependencies = [
2126
+
{ name = "typing-extensions" },
2127
+
]
2128
+
sdist = { url = "https://files.pythonhosted.org/packages/b7/48/af6173dbca4454f4637a4678b67f52ca7e0c1ed7d5894d89d434fecede05/grpcio-1.80.0.tar.gz", hash = "sha256:29aca15edd0688c22ba01d7cc01cb000d72b2033f4a3c72a81a19b56fd143257", size = 12978905, upload-time = "2026-03-30T08:49:10.502Z" }
2129
+
wheels = [
2130
+
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2131
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2132
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2133
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2134
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2135
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2136
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2137
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2138
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2139
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2140
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2141
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2142
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2143
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2144
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2145
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2146
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1045
2183
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1131
2269
1132
2270
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2277
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2278
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2279
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2280
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2281
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2282
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2299
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1151
2301
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1152
2302
1153
2303
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1183
2333
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1184
2334
1185
2335
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1203
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2605
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1323
2606
1324
2607
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1395
2691
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1396
2692
1397
2693
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1604
3502
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3503
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4751
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4757
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4758
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4759
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4760
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[[package]]
4761
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4762
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4763
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4764
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1901
4767
]
1902
4768
1903
4769
[[package]]
···
1922
4788
]
1923
4789
1924
4790
[[package]]
4791
+
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4792
+
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4793
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4797
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4798
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4799
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4800
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4801
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4802
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4803
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4804
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4805
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4806
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4807
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4808
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4810
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4811
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4812
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[[package]]
4813
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4814
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4815
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4816
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4817
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4818
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4819
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4820
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4822
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4823
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4824
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[[package]]
1925
4825
name = "pillow"
1926
4826
version = "12.1.0"
1927
4827
source = { registry = "https://pypi.org/simple" }
···
2020
4920
]
2021
4921
2022
4922
[[package]]
4923
+
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4924
+
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4925
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4926
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4927
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4928
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4929
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4930
+
4931
+
[[package]]
2023
4932
name = "playwright"
2024
4933
version = "1.58.0"
2025
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2094
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5282
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5283
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···
2254
5441
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2255
5442
2256
5443
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5444
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5445
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5451
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2257
5453
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2258
5454
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2259
5455
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···
2293
5489
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2294
5490
2295
5491
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5492
+
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5493
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5494
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5502
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5505
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5506
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2296
5507
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2297
5508
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2298
5509
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···
2303
5514
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2304
5515
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5517
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5518
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5519
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5520
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5522
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2306
5526
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2307
5527
2308
5528
[[package]]
···
2430
5650
]
2431
5651
2432
5652
[[package]]
5653
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5654
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5660
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5669
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5670
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5671
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2433
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5673
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2435
5674
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5675
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5680
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5688
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5689
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5699
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2439
5700
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2440
5701
2441
5702
[[package]]
···
2503
5764
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2504
5765
2505
5766
[[package]]
5767
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5768
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6014
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6015
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2610
6016
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2611
6017
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2612
6018
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2619
6025
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2620
6026
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2621
6027
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6028
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6029
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6030
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6031
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6032
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6033
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6034
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6035
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6036
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6037
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6038
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6039
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6040
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2622
6042
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2623
6043
2624
6044
[[package]]
···
2769
6189
]
2770
6190
2771
6191
[[package]]
6192
+
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6193
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6194
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6627
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6628
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6629
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6630
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6631
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6632
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6633
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6634
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6635
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6636
+
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6637
+
6638
+
[[package]]
6639
+
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6640
+
version = "2.58.0"
6641
+
source = { registry = "https://pypi.org/simple" }
6642
+
dependencies = [
6643
+
{ name = "certifi" },
6644
+
{ name = "urllib3" },
6645
+
]
6646
+
sdist = { url = "https://files.pythonhosted.org/packages/26/b3/fb8291170d0e844173164709fc0fa0c221ed75a5da740c8746f2a83b4eb1/sentry_sdk-2.58.0.tar.gz", hash = "sha256:c1144d947352d54e5b7daa63596d9f848adf684989c06c4f5a659f0c85a18f6f", size = 438764, upload-time = "2026-04-13T17:23:26.265Z" }
6647
+
wheels = [
6648
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{ url = "https://files.pythonhosted.org/packages/fa/eb/d875669993b762556ae8b2efd86219943b4c0864d22204d622a9aee3052b/sentry_sdk-2.58.0-py2.py3-none-any.whl", hash = "sha256:688d1c704ddecf382ea3326f21a67453d4caa95592d722b7c780a36a9d23109e", size = 460919, upload-time = "2026-04-13T17:23:24.675Z" },
6649
+
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6650
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6651
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[[package]]
3043
6652
name = "setproctitle"
3044
6653
version = "1.3.7"
3045
6654
source = { registry = "https://pypi.org/simple" }
···
3163
6772
]
3164
6773
3165
6774
[[package]]
6775
+
name = "smmap"
6776
+
version = "5.0.3"
6777
+
source = { registry = "https://pypi.org/simple" }
6778
+
sdist = { url = "https://files.pythonhosted.org/packages/1f/ea/49c993d6dfdd7338c9b1000a0f36817ed7ec84577ae2e52f890d1a4ff909/smmap-5.0.3.tar.gz", hash = "sha256:4d9debb8b99007ae47165abc08670bd74cb74b5227dda7f643eccc4e9eb5642c", size = 22506, upload-time = "2026-03-09T03:43:26.1Z" }
6779
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wheels = [
6780
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{ url = "https://files.pythonhosted.org/packages/c1/d4/59e74daffcb57a07668852eeeb6035af9f32cbfd7a1d2511f17d2fe6a738/smmap-5.0.3-py3-none-any.whl", hash = "sha256:c106e05d5a61449cf6ba9a1e650227ecfb141590d2a98412103ff35d89fc7b2f", size = 24390, upload-time = "2026-03-09T03:43:24.361Z" },
6781
+
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6782
+
6783
+
[[package]]
3166
6784
name = "sniffio"
3167
6785
version = "1.3.1"
3168
6786
source = { registry = "https://pypi.org/simple" }
···
3227
6845
{ name = "userpath" },
3228
6846
{ name = "weasyprint" },
3229
6847
{ name = "websockets" },
6848
+
]
6849
+
6850
+
[package.optional-dependencies]
6851
+
parakeet-nemo = [
6852
+
{ name = "nemo-toolkit", extra = ["asr"] },
6853
+
{ name = "torch" },
3230
6854
]
3231
6855
3232
6856
[package.metadata]
···
3250
6874
{ name = "markdown" },
3251
6875
{ name = "mistune" },
3252
6876
{ name = "mypy" },
6877
+
{ name = "nemo-toolkit", extras = ["asr"], marker = "extra == 'parakeet-nemo'" },
3253
6878
{ name = "numpy" },
3254
6879
{ name = "onnxruntime", specifier = ">=1.19" },
3255
6880
{ name = "openai", specifier = ">=1.2.0" },
···
3275
6900
{ name = "setproctitle" },
3276
6901
{ name = "soundfile" },
3277
6902
{ name = "timefhuman" },
6903
+
{ name = "torch", marker = "extra == 'parakeet-nemo'" },
3278
6904
{ name = "typer" },
3279
6905
{ name = "tzlocal" },
3280
6906
{ name = "userpath", specifier = ">=1.9.2,<2" },
3281
6907
{ name = "weasyprint" },
3282
6908
{ name = "websockets", specifier = ">=13.0" },
3283
6909
]
6910
+
provides-extras = ["parakeet-nemo"]
6911
+
6912
+
[[package]]
6913
+
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6914
+
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6915
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6916
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sdist = { url = "https://files.pythonhosted.org/packages/e8/c4/ba2f8066cceb6f23394729afe52f3bf7adec04bf9ed2c820b39e19299111/sortedcontainers-2.4.0.tar.gz", hash = "sha256:25caa5a06cc30b6b83d11423433f65d1f9d76c4c6a0c90e3379eaa43b9bfdb88", size = 30594, upload-time = "2021-05-16T22:03:42.897Z" }
6917
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wheels = [
6918
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6919
+
]
3284
6920
3285
6921
[[package]]
3286
6922
name = "soundfile"
···
3303
6939
]
3304
6940
3305
6941
[[package]]
6942
+
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6943
+
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6944
+
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6945
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6946
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6947
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6948
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{ name = "typing-extensions" },
6949
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6950
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6951
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6952
+
[[package]]
6953
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6954
+
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6955
+
source = { registry = "https://pypi.org/simple" }
6956
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dependencies = [
6957
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{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
6958
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{ name = "numpy", version = "2.3.5", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
6959
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6960
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6961
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wheels = [
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6963
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6964
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6965
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6966
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6967
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6968
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6969
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6970
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6971
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6972
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6973
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6974
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6975
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6976
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6977
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6978
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6979
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6980
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6981
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6982
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6983
+
6984
+
[[package]]
6985
+
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3412
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3492
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3493
7464
3494
7465
[[package]]
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7466
+
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3496
7467
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3497
7468
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3498
7469
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3499
7470
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7471
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7472
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3500
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3505
7478
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3506
7479
3507
7480
[[package]]
···
3568
7541
]
3569
7542
3570
7543
[[package]]
7544
+
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7545
+
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7546
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7551
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7552
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7553
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7554
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7555
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7556
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7572
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3571
7573
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3572
7574
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3573
7575
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···
3593
7595
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7600
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7602
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7603
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3596
7613
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3597
7614
3598
7615
[[package]]
···
3676
7693
]
3677
7694
3678
7695
[[package]]
7696
+
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7697
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7700
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7701
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7715
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3679
7716
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3680
7717
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3681
7718
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···
3832
7869
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3833
7870
3834
7871
[[package]]
7872
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7873
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